Has anyone ever produced an insight from data and analytics that no one acted on?

That was the question posed by former US Department of Health and Human Services Chief Technology Officer Bryan Sivak at a recent health analytics forum. Sivak answered that question with a firm yes – and made the case that nearly all health care organizations have failed to act on their data and the insight from analytics.

Sivak listed four reasons why, despite all the promise of (and investment in) analytics, the health care industry does not act on the insights that are produced. The first three? Audience, message and processes – and getting them organized around analytics-derived insights. The fourth focuses on the importance of the right incentives.

Getting incentives right may be the trickiest of the four. As health care evolves, the only constant seems to be incentive-driven behavior that traditionally doesn’t align with patient outcomes.

Incentives strongly influence behavior, no matter the circumstance. Currently, the health care industry doesn’t use the right incentives to embrace the insights that could expand and clarify choices, increase efficiency, decrease costs and generally improve the quality of care.

Fortunately, there is some forward momentum in some pockets in the US, especially due to recent health care reforms. For example, care from readmissions within 30 days of discharge (for any reason) are no longer paid for by Medicare or Medicaid. This is causing health care systems to look at their data carefully to predict what care modifications can decrease patient readmissions.

Change is overdue and inevitable. But to compel that change, you must alter the way you think and how you make decisions across the board. This involves aligning the incentives that drive behavior. The other part, as Sivak pointed out, is about communicating clear information to patients to help them make better decisions about their own care.

So how can data and analytics help? For starters, it can sift through high volumes of information, extract key insights and map them back to one another in meaningful ways. Think about how you identify a primary care doctor. You can go to your provider’s website and search according to a set of criteria, such as the doctor’s credentials, their office location and the health plans they accept.

These criteria are focused primarily on convenience, not the level of care. They do not necessarily align with the best patient outcomes. The existing criteria doesn’t equip the patient with the knowledge to make an informed decision based on their specific needs – resulting in choices that do not always produce the best outcomes.

When health care information is focused around quality criteria, everything gets better. In one example, emergency rooms that sent patients home with only a list of random follow-up care facilities saw a 25 percent re-admittance rate.

What happened is no surprise. Patients often choose a facility closer to their home, a choice unrelated to their care needs. This was an inefficient method that led to increased costs and a trust gap between patient, doctor and provider. When emergency rooms sent patients home with data about outcomes, the quality of care and customer satisfaction, re-admittance rates plummeted – and 82 percent of patients reported high levels of satisfaction with the chosen facility.

What changed? Data helped the patients change their behavior. And health care providers are rewarded for quality care and insurance providers benefit from decreased patient costs.

Of course, influencing the entire health care industry to embrace data analytics isn’t as simple as sharpening its information products. While you may know the solution for health care woes, big institutions change slowly.

In his talk, Sivak asked how to take a hierarchical, command-and-control-oriented, risk-averse, old-school organization – and transform it into a modern and flexible one.

Process. To change a massive institution, you must show them how. That means coming to the table with processes that have already been developed, tested and proven to work. Sivak pointed out that technology and innovation have the power to make the world work better for everyone. Getting there is just a matter of considering process from a birds-eye view and being methodical, deliberate and collaborative in our strategy.

As a Product Marketing Consultant at SAS, Steve Bennett drives strategic industry positioning and messaging in global Government markets. A thought leader in decision science and the application of analytics in Government, Steve works to enable delivery of effective solutions to Government customers around the world.